Power system power supply planning method based on electricity-carbon-hydrogen cooperation and terminal

Abstract

The invention discloses an electric power system power supply planning method based on electricity-carbon-hydrogen cooperation and a terminal, and the method comprises the steps: building a first objective function which takes the minimum total investment cost of a system planning period of an electric power system as an objective, and setting an installation scale constraint, an electric power margin constraint and an annual investment net profit constraint which belong to the first objective function; establishing a second objective function, wherein the second objective function comprises a cost function with minimum operation cost and carbon emission cost as a target and a market clearing function with minimum market transaction income as a target; creating a new energy output prediction error constraint corresponding to the power system, and integrating the first target function, the second target function and the new energy output prediction error constraint to obtain a system planning model; and obtaining an input variable, and solving the system planning model. The new energy consumption is promoted while the economic cost is controlled, the uncertainty of new energy output is fully considered, and the safety of the power grid and the economical efficiency of a power generation main body are comprehensively planned.

Description

Technical Field

[0001] The present invention relates to the field of integrated energy systems, and in particular to a method and terminal for power system power planning based on electricity-carbon-hydrogen synergy. Background Art

[0002] The challenges faced by the base-based development and utilization of new energy include several aspects: First, the matching degree between the peak periods of new energy generation and load demand is low, and the system's regulatory resources are insufficient. It is urgent to explore new modes and methods for local consumption such as green electricity hydrogen production to avoid further deterioration of the consumption problem; second, the system inertia is reduced under the large-scale grid connection of new energy, and the problems of system synchronous stability and new form stability are superimposed; third, under the dual carbon goals, the functional positioning of thermal power has changed, and under the coupling of the electricity market and the carbon market, the value of supporting power sources and new energy needs to be further released, so as to guide power supply companies and other market entities to invest and operate with reliable economy.

[0003] To this end, current research on power supply planning is mainly focused on how to accommodate a high proportion of new energy in the most economical way to form a reasonable power supply structure and ensure system safety. Summary of the invention

[0004] The technical problem to be solved by the present invention is to propose a power system power supply planning method and terminal based on electricity-carbon-hydrogen synergy, promote the consumption of new energy while controlling economic costs, and ensure system safety.

[0005] In order to solve the above technical problems, the technical solution adopted by the present invention is:

[0006] The power system power planning method based on electricity-carbon-hydrogen synergy includes the following steps:

[0007] S1. Establishing a first objective function with the goal of minimizing the total investment cost of the power system during the system planning period, and setting an installed capacity constraint, a power margin constraint, and an annual investment net profit constraint subordinate to the first objective function;

[0008] S2. Establishing a second objective function, wherein the second objective function includes a cost function with the goal of minimizing operating costs and carbon emission costs and a market clearing function with the goal of minimizing market transaction revenue;

[0009] S3, creating a new energy output prediction error constraint corresponding to the power system, integrating the first objective function, the second objective function and the new energy output prediction error constraint, and obtaining a system planning model;

[0010] S4. Obtain input variables and solve the system planning model.

[0011] In order to solve the above technical problems, another technical solution adopted by the present invention is:

[0012] An electric power system power supply planning terminal based on electricity-carbon-hydrogen synergy includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the above-mentioned electric power system power supply planning method based on electricity-carbon-hydrogen synergy is implemented.

[0013] The beneficial effects of the present invention are: providing an electric power system power supply planning method and terminal based on electricity-carbon-hydrogen synergy, creating a first objective function, minimizing the input cost under the premise of satisfying the installed capacity constraints, power margin constraints and annual investment net profit constraints, and combining the cost function with the minimum operating cost and carbon emission cost as the goal and the market clearing function with the minimum market transaction profit as the goal, to establish a system planning model, control the minimization of operating costs and market profits, thereby promoting the consumption of new energy while controlling economic costs, fully considering the uncertainty of new energy output, ensuring that the model is sufficiently accurate, and coordinating the safety of the power grid and the economy of the power generation entity. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] Figure 1 It is a schematic diagram of the steps of the power system power planning method based on electricity-carbon-hydrogen synergy of the present invention;

[0015] Figure 2 This is a system block diagram of the power system power planning terminal based on electricity-carbon-hydrogen synergy of the present invention.

[0016] Description of labels:

[0017] 1. Power system power planning terminal based on electricity-carbon-hydrogen synergy; 2. Memory; 3. Processor. DETAILED DESCRIPTION

[0018] In order to explain the technical content, achieved objectives and effects of the present invention in detail, the following is an explanation in conjunction with the implementation modes and the accompanying drawings.

[0019] Please refer to Figure 1 , a power system power planning method based on electricity-carbon-hydrogen synergy includes the following steps:

[0020] S1. Establishing a first objective function with the goal of minimizing the total investment cost of the power system during the system planning period, and setting an installed capacity constraint, a power margin constraint, and an annual investment net profit constraint subordinate to the first objective function;

[0021] S2. Establishing a second objective function, wherein the second objective function includes a cost function with the goal of minimizing operating costs and carbon emission costs and a market clearing function with the goal of minimizing market transaction revenue;

[0022] S3, creating a new energy output prediction error constraint corresponding to the power system, integrating the first objective function, the second objective function and the new energy output prediction error constraint, and obtaining a system planning model;

[0023] S4. Obtain input variables and solve the system planning model.

[0024] From the above description, it can be seen that the beneficial effects of the present invention are: creating a first objective function to minimize the input cost under the premise of satisfying the installed capacity constraints, power margin constraints and annual investment net profit constraints, and at the same time combining the cost function with the minimum operating cost and carbon emission cost as the goal and the market clearing function with the minimum market transaction profit as the goal, to establish a system planning model, control the minimization of operating costs and market profits, thereby promoting the consumption of new energy while controlling economic costs, fully considering the uncertainty of new energy output, ensuring that the model is accurate enough, and coordinating the safety of the power grid and the economy of the power generation entity.

[0025] Furthermore, the first objective function is expressed as follows:

[0026] min:f inv +f fix -f cap ;

[0027] Among them, f inv 、f fix 、f cap Respectively represent investment cost, fixed maintenance cost and capacity compensation cost of thermal power units;

[0028] Investment cost:

[0029]

[0030] Fixed maintenance costs:

[0031]

[0032] Capacity compensation costs for thermal power units:

[0033]

[0034] in, Respectively represent the collection of thermal power units, wind power, photovoltaic, electrolyzer and hydrogen storage tank to be built, Ω g ,Ω w ,Ω pv Respectively represent the collection of thermal power units, wind power and photovoltaic units in service; P i g , P i w , P i pv, P i PEM , P i HST Respectively represent the rated capacity of thermal power units, wind power, photovoltaic, electrolyzer and hydrogen storage tank, Represent the unit capacity investment costs of thermal power units, wind power, photovoltaics, electrolyzers and hydrogen storage tanks, respectively. Represent the fixed maintenance costs per unit capacity of thermal power units, wind power, photovoltaics, electrolyzers and hydrogen storage tanks, respectively. It is a 0-1 integer variable, which represents the status of thermal power units, wind power, photovoltaic and hydrogen production and storage equipment respectively. The value of the thermal power units and renewable energy units in operation is 1. For the thermal power units, renewable energy units, electrolyzers and hydrogen storage tanks to be selected, when the value is 1, it means construction is in progress, and when the value is 0, it means no construction is in progress. is the unit capacity compensation price of thermal power units, P i g,com Indicates the compensation capacity of thermal power units, μ i g , μ i w , μ i pv , μ i PWM , μ i HST represents the capital recovery coefficient of thermal power units, wind power, photovoltaic, electrolyzer and hydrogen storage tank respectively, and i represents the equipment variable;

[0035] and:

[0036]

[0037] Where r is the discount rate, N i Indicates the age of the equipment.

[0038] From the above description, it can be seen that in response to a multi-category power system composed of thermal power units, wind power, photovoltaics, electrolyzers and hydrogen storage tanks, it is necessary to comprehensively consider each type of equipment from multiple aspects such as rated capacity, unit capacity investment cost, and whether to invest in construction, so as to accurately and comprehensively control the system's investment cost and strive to minimize it.

[0039] Furthermore, the installed capacity constraints include the maximum construction capacity constraints of coal-fired power units, the maximum construction capacity constraints of photovoltaic power, the maximum construction capacity constraints of wind power, the maximum construction capacity constraints of electrolyzers and the maximum construction capacity constraints of hydrogen storage tanks.

[0040] From the above description, it can be seen that when controlling the investment cost, capacity constraints are introduced one by one according to the different types of power supplies included in the system to avoid the situation where some equipment exceeds the maximum allowable construction capacity during planning.

[0041] Furthermore, the power margin constraint includes:

[0042]

[0043] Among them, Ω h ,Ω d Respectively represent the DC line and load node set, P i h,max ,P i d,max They represent the maximum active transmission power of the DC line and the maximum load of the node, respectively, pv ,x w They represent the confidence capacity coefficients of photovoltaic and wind power respectively, and R is the reserve capacity coefficient.

[0044] From the above description, we can see that while controlling costs, sufficient power margin should be reserved to cope with some unexpected situations and ensure power supply stability.

[0045] Furthermore, the annual investment net profit constraint includes:

[0046]

[0047] Among them, s and t represent the operation scenario and time period respectively, λ d , PEM , ccer Respectively represent the node marginal electricity price, the expected price of hydrogen and the clearing price, N s is the number of scenes, They represent the operating cost and carbon emission cost of thermal power units respectively; They represent the active output of thermal power units, photovoltaic units, and wind power units, the active load of the load node, and the active power of the electrolyzer.

[0048] Furthermore, the step S2 comprises:

[0049] S21. Create a cost function with the goal of minimizing operating costs and carbon emission costs:

[0050] minf ope +f car ;

[0051]

[0052] Among them, Ω t ,Ω s Respectively represent the running time period and the running scene set, f ope 、f car Represent the total operating cost and total carbon emission cost of the system respectively, They represent the coefficients of the power generation cost of thermal power units, Indicates the active power and apparent power of the thermal power unit. They represent the constant term and slope of the CEI curve of thermal power units, is the industry benchmark value for thermal power units, O car represents the carbon emission quota price, It is a 0-1 integer variable, indicating the start and stop status of the thermal power unit. A value of 1 indicates that it is in the start-up state, and a value of 0 indicates that it is in the shutdown state.

[0053] S22. Setting power balance condition constraints, unit operation constraints, DC operation constraints, line transmission power constraints, electrolyzer operation constraints, and hydrogen storage tank operation constraints that are subordinate to the cost function.

[0054] From the above description, it can be seen that the low-carbon economic power supply planning can be achieved by comprehensively considering the minimization of operating costs and carbon emission costs.

[0055] Furthermore, the step S2 comprises:

[0056] S23. Create a market clearing function with the goal of minimizing market transaction returns:

[0057]

[0058] in, Represent the buying and selling prices of renewable energy, They respectively represent the buying and selling volumes of market entities.

[0059] S24. Setting a transaction quantity consistency constraint, an offset ratio upper limit constraint, a selling quantity constraint, and a carbon dioxide emission reduction constraint that are subordinate to the market clearing function.

[0060] From the above description, we can see that it is necessary to strictly control the market transaction to minimize the benefits, maximize social welfare, promote the consumption of new energy, and form a reasonable power supply structure.

[0061] Further, the creating of the new energy output prediction error constraint corresponding to the power system includes:

[0062] The budget uncertainty set is created to characterize the error constraints of the new energy output forecast:

[0063]

[0064] in, represents the wind power prediction error, Photovoltaic prediction error, and are the boundary adjustment values ​​of the budget uncertainty set composed of the actual output of wind power and photovoltaic power, respectively, to control the conservatism of uncertain parameters, is the total wind and solar prediction error of the system; The number of wind turbines to be built. is the number of photovoltaics.

[0065] From the above description, we can see that the use of budget uncertainty set can exclude some extremely low probability events and reduce the conservatism of decision-making.

[0066] Furthermore, the system planning model:

[0067]

[0068] z is the investment and construction decision of thermal power units, wind power, photovoltaic and hydrogen production and storage equipment, f1(z) represents the first objective function, f2(y) is the objective function of the second stage, and y is the input variable of the second objective function. Indicates that The expected function of the maximum risk value under the conditions.

[0069] From the above description, it can be seen that by integrating the first objective function and the second objective function, the power supply planning of the electric-carbon-hydrogen coordinated power system with multiple constraints is realized. At the same time, an expectation function with a large risk value is set so that the operation decision can cope with the risks in the operation scenario, making the operation decision more robust.

[0070] Please refer to Figure 2 The power system power planning terminal 1 based on electricity-carbon-hydrogen synergy includes a memory 2, a processor 3, and a computer program stored in the memory 2 and executable on the processor 3. When the processor 3 executes the computer program, the power system power planning method based on electricity-carbon-hydrogen synergy is implemented.

[0071] From the above description, it can be seen that the beneficial effects of the present invention are: creating a first objective function to minimize the input cost under the premise of satisfying the installed capacity constraints, power margin constraints and annual investment net profit constraints, and at the same time combining the cost function with the minimum operating cost and carbon emission cost as the goal and the market clearing function with the minimum market transaction profit as the goal, to establish a system planning model, control the minimization of operating costs and market profits, thereby promoting the consumption of new energy while controlling economic costs, fully considering the uncertainty of new energy output, ensuring that the model is accurate enough, and coordinating the safety of the power grid and the economy of the power generation entity.

[0072] Please refer to Figure 1 , Embodiment 1 of the present invention is:

[0073] The power system power planning method based on electricity-carbon-hydrogen synergy includes the following steps:

[0074] S1. Establish a first objective function with the goal of minimizing the total investment cost of the power system during the system planning period, and set the installed capacity constraint, power margin constraint and annual investment net profit constraint subordinate to the first objective function;

[0075] Specifically, the first objective function is expressed as follows:

[0076] min:f inv +f fix -f cap (1)

[0077] Among them, f inv ,f fix ,f cap They respectively represent investment cost, fixed maintenance cost and capacity compensation cost of thermal power units; investment cost refers to the total investment cost of supporting coal-fired power units, wind and solar new energy units and hydrogen production and storage equipment.

[0078] Specifically, the investment cost f inv :

[0079]

[0080] Fixed maintenance cost fix :

[0081]

[0082] Capacity compensation fee for thermal power unitsf cap :

[0083]

[0084] in, Respectively represent the collection of thermal power units, wind power, photovoltaic, electrolyzer and hydrogen storage tank to be built, Ω g ,Ω w ,Ω pv Respectively represent the collection of thermal power units, wind power and photovoltaic units in service; P i g , P i w , P i pv , P i PEM , P i HST Respectively represent the rated capacity of thermal power units, wind power, photovoltaic, electrolyzer and hydrogen storage tank, Represent the unit capacity investment costs of thermal power units, wind power, photovoltaics, electrolyzers and hydrogen storage tanks, respectively. Represent the fixed maintenance costs per unit capacity of thermal power units, wind power, photovoltaics, electrolyzers and hydrogen storage tanks, respectively. Represent the fixed maintenance costs per unit capacity of thermal power units, wind power, photovoltaics, electrolyzers and hydrogen storage tanks, respectively. It is a 0-1 integer variable, which represents the status of thermal power units, wind power, photovoltaic and hydrogen production and storage equipment respectively. The value of the thermal power units and renewable energy units in operation is 1. For the thermal power units, renewable energy units, electrolyzers and hydrogen storage tanks to be selected, when the value is 1, it means construction is in progress, and when the value is 0, it means no construction is in progress. is the unit capacity compensation price of thermal power units, P i g,com Indicates the compensation capacity of thermal power units, μ i g , μ i w , μ i pv , μ i PWM , μ i HST represents the capital recovery coefficient of thermal power units, wind power, photovoltaic, electrolyzer and hydrogen storage tank respectively, and i represents the equipment variable;

[0085] and:

[0086]

[0087] Where r is the discount rate, N i Indicates the age of the equipment.

[0088] In this embodiment, the installed capacity constraints include the maximum construction capacity constraints of coal-fired power units, the maximum construction capacity constraints of photovoltaic power, the maximum construction capacity constraints of wind power, the maximum construction capacity constraints of electrolyzers, and the maximum construction capacity constraints of hydrogen storage tanks.

[0089] Due to the limitation of engineering construction technology, the capacity of supporting coal-fired power, new energy and hydrogen production and storage equipment newly built in each cycle needs to be limited to a certain range; among them, the maximum construction capacity constraint of coal-fired power units is expressed as:

[0090]

[0091] The maximum photovoltaic construction capacity constraint is expressed as:

[0092]

[0093] The maximum construction capacity constraint of wind power is expressed as:

[0094]

[0095] The maximum construction capacity constraint of the electrolyzer is expressed as:

[0096]

[0097] The maximum construction capacity constraint of hydrogen storage tank is expressed as:

[0098]

[0099] Among them, P g,max , P pv,max , P w,max , P PEM,max , P HST,max Indicates the maximum construction capacity allowed for coal-fired power units, photovoltaics, wind power, electrolyzers and hydrogen storage tanks.

[0100] In this embodiment, the power margin constraint includes:

[0101]

[0102] Among them, Ω h ,Ω d Respectively represent the DC line and load node set, P i h,max , P i d,max They represent the maximum active transmission power of the DC line and the maximum load of the node, respectively, pv , χ w They represent the confidence capacity coefficients of photovoltaic and wind power respectively, and R is the reserve capacity coefficient.

[0103] The annual net investment net profit constraints include:

[0104]

[0105] Among them, s and t represent the operation scenario and time period respectively, λ d , PEM , ccer Respectively represent the node marginal electricity price, the expected price of hydrogen and the clearing price, N s is the number of scenes, f s o 、f s car Respectively represent the operating cost and carbon emission cost of thermal power units, They represent the active output of thermal power units, photovoltaic units, and wind power units, the active load of the load node, and the active power of the electrolyzer.

[0106] S2. Establishing a second objective function, which includes a cost function with the goal of minimizing operating costs and carbon emission costs and a market clearing function with the goal of minimizing market transaction revenue;

[0107] In this embodiment, the first objective function is used as the upper model, and the cost function and the market clearing function together constitute the lower model, which specifically includes:

[0108] S21. Create a cost function with the goal of minimizing operating costs and carbon emission costs:

[0109] minf ope +f car (13)

[0110]

[0111] Among them, Ω t ,Ω s Respectively represent the running time period and the running scene set, f ope 、f car Represent the total operating cost and total carbon emission cost of the system respectively, They represent the coefficients of the power generation cost of thermal power units, Indicates the active power and apparent power of the thermal power unit. They represent the constant term and slope of the CEI curve of thermal power units, is the industry benchmark value for thermal power units, O car represents the carbon emission quota price, It is a 0-1 integer variable, indicating the start and stop status of the thermal power unit. When the value is 1, it indicates that it is in the start-up state, and when the value is 0, it indicates the shutdown state.

[0112] S22. Set power balance condition constraints, unit operation constraints, DC operation constraints, line transmission power constraints, electrolyzer operation constraints, and hydrogen storage tank operation constraints that are subordinate to the cost function, as follows:

[0113] (1) Power balance conditions

[0114]

[0115] in, They respectively represent the active output of thermal power units, photovoltaic units, and wind power units, the active transmission power of DC lines, the active power of load nodes, and the power of electrolyzers.

[0116] (2) Unit operation constraints

[0117]

[0118]

[0119] Among them, P i g,min , P i g,max They represent the minimum active output and maximum active output of thermal power unit i respectively; Represent the output forecast values ​​of wind power and photovoltaic power, They represent the maximum landslide power and climbing power of thermal power unit i per unit time, Respectively represent the minimum start and stop duration. Constraints (17)-(19) respectively represent that the active output of thermal power units, photovoltaic and wind power units must meet technical requirements. Constraint (20) represents that the active output of thermal power units in two adjacent time periods must meet the climbing and sliding constraints. Constraints (21)-(22) represent that thermal power units must meet the minimum operation and shutdown time limits.

[0120] (3) DC operation constraints

[0121] Considering that most of the current UHV DC lines are conventional DC, they are easily restricted by the thermal stability limit of the conductor and the polarity change characteristics of the phase-commutating converter. In daily operation, the flow direction of the UHV DC transmission line should not change frequently, and the number of adjustments within a day is limited. In addition, the DC line needs to meet the DC operating power constraints, DC power ramp constraints and DC power adjustment constraints during operation. The specific constraints are as follows:

[0122]

[0123] Where P i h,min , P i h,max Indicates the minimum operating power and rated active power of the DC line. Indicates whether the DC line adjusts power downward or upward (0 means no action, 1 means action), U i,s,t Indicates whether the DC line performs power adjustment in period t (0 means no action, 1 means action). They represent the maximum landslide power and climbing power of the DC line per unit time respectively; Represents the minimum time that the DC line operates at a certain constant power, N h ,max Indicates the maximum power adjustment times of the DC line in one day.

[0124] Constraint (23) means that the DC operating power needs to be maintained within the maximum and minimum operating power range. Constraint (24) means that the DC active power change in adjacent time periods must meet the climbing and sliding restrictions. Constraint (25) means that the DC is not allowed to perform reverse power adjustment in adjacent time periods. Constraints (26) and (27) respectively mean that the DC must meet the minimum constant power operation time limit and the maximum number of power flow adjustments within a day.

[0125] (4) Line transmission power constraints

[0126]

[0127] -π≤θ i,s,t,θ j,s,t ≤π (29)

[0128] in, represents the active power transmission limit of line k, θ i,s,t are the phase angles of line conductance and node voltage respectively.

[0129] (5) Electrolyzer operation constraints

[0130]

[0131] Among them, m represents the number of segments, and M represents the set of segment numbers; is a 0-1 integer variable, representing the operation, shutdown and standby state of the electrolyzer, respectively. PEM,min , P PEM,sb , P PEM,max They respectively represent the minimum power consumption, maximum power consumption and standby power consumption of the electrolytic cell.

[0132] Constraint (30) is the mutually exclusive constraint of the electrolytic cell's operating state, that is, it can only be in operation, standby, and shutdown; constraint (31) is the power constraint of the electrolytic cell in operation, standby, and shutdown states; constraint (32) defines the cold start state Indicates that the electrolyzer is switched from shutdown state to operation state.

[0133] Considering the nonlinear relationship between the hydrogen production efficiency and input power of the PEM electrolyzer, the electrolysis efficiency is highest when its per-unit power is close to 0.37. For the convenience of calculation, the piecewise linearization method is used to approximate the relationship between the hydrogen production H and the input power P of the PEM electrolyzer in each segment. The expression is:

[0134]

[0135] The segmented operation constraints are expressed as:

[0136]

[0137] (6) Hydrogen storage tank operation modeling

[0138]

[0139]

[0140] in, Indicates the remaining hydrogen volume of the hydrogen storage tank, the gas output of the hydrogen storage tank, the minimum technical hydrogen storage volume, the maximum technical hydrogen storage volume, τ i,s,t It is an integer variable. When the value is 1, it indicates that the hydrogen storage tank is in the intake state, and when the value is 0, it indicates that it is in the exhaust state.

[0141] S23. Create a market clearing function with the goal of minimizing market transaction returns:

[0142]

[0143] in, Represent the buying and selling prices of renewable energy, They respectively represent the buying and selling volumes of market entities.

[0144] S24. Set the transaction quantity consistency constraint, offset ratio upper limit constraint, selling quantity constraint and carbon dioxide emission reduction constraint subordinate to the market clearing function, as follows:

[0145] (1) Consistency constraints on transaction quantities, i.e., consistency constraints on transaction quantities in the CCER (certified voluntary emission reduction) market:

[0146]

[0147] (2) Offset ratio upper limit constraint, that is, the amount that power generation enterprises can purchase shall not exceed the CCER offset ratio upper limit constraint:

[0148]

[0149] (3) Sales quantity constraint, that is, the number of CCERs that power generation companies can sell is a non-negative constraint:

[0150]

[0151] (4) CO2 emission reduction constraints, i.e. CO2 emission reduction constraints for renewable energy power generation

[0152]

[0153] in, Indicates the output of the thermal power unit on the previous day, μ ccer Indicates the highest offset ratio of CCER; F OM 、F BM They represent the marginal emission factor of electricity quantity and the marginal emission factor of capacity respectively.

[0154] S3, creating a new energy output forecast error constraint corresponding to the power system, integrating the first objective function, the second objective function and the new energy output forecast error constraint, and obtaining a system planning model;

[0155] In this embodiment, creating a new energy output prediction error constraint corresponding to the power system includes:

[0156] Create a budget uncertainty set to characterize the error constraints on renewable energy output forecasts:

[0157]

[0158] in, represents the wind power prediction error, Photovoltaic prediction error, and are the boundary adjustment values ​​of the budget uncertainty set composed of the actual output of wind power and photovoltaic power, respectively, to control the conservatism of uncertain parameters, is the total wind and solar prediction error of the system, The number of wind turbines to be built. is the number of photovoltaics.

[0159] In this embodiment, the system planning model:

[0160]

[0161] Among them, z is the investment and construction decision of thermal power units, wind power, photovoltaic and hydrogen production and storage equipment, f1(z) represents the first objective function, f2(y) is the objective function of the second stage, and y is the input variable of the second objective function. For The expected function of the maximum risk value under certain conditions enables operation decisions to cope with the risks in operation scenarios, making operation decisions more robust.

[0162] S4. Obtain input variables and solve the system planning model.

[0163] In this embodiment, the system planning model is an economic dispatch model based on distributed robust optimization, which is difficult to solve directly. The expected function representing the maximum risk value is Due to being in Under these conditions, it is a difficult-to-handle item, so the complex model needs to be simplified into a simple model that is easy to solve. The specific processing is as follows:

[0164] According to the duality theory, equation (47) can be transformed into:

[0165]

[0166] Since the budget uncertainty set belongs to a polyhedron, the optimal value of (48) will be obtained at the boundary value of the budget uncertainty set, and then formula (48) can be transformed into the following form:

[0167]

[0168] in, is an auxiliary variable, ρ s,t is the dual variable.

[0169] In formula (49), and Hidden nonlinear terms and It is difficult to solve. We can use the principle of exterior approximation to transform problem (49) into a linear formula:

[0170]

[0171] The above model is a general two-layer robust optimization model, which can be solved by a two-layer optimization algorithm.

[0172] Please refer to Figure 2 , Embodiment 2 of the present invention is:

[0173] The power system power planning terminal 1 based on electricity-carbon-hydrogen synergy includes a memory 2, a processor 3, and a computer program stored in the memory 2 and executable on the processor 3. When the processor 3 executes the computer program, the power system power planning method based on electricity-carbon-hydrogen synergy of embodiment 1 is implemented.

[0174] In summary, the power system power planning method and terminal based on electricity-carbon-hydrogen synergy provided by the present invention create a first objective function to minimize the input cost under the premise of satisfying the installed capacity constraints, power margin constraints and annual investment net profit constraints, and at the same time, combine the cost function with the minimum operating cost and carbon emission cost as the goal and the market clearing function with the minimum market transaction profit as the goal to establish a system planning model to control the minimization of operating costs and market profits. In this way, while controlling the economic cost, the uncertainty of new energy output is fully considered to make the model more accurate. At the same time, because the plan takes into account the capacity compensation electricity price, carbon tax price and green certificate trading price of thermal power units, the power planning plan can promote the local consumption of new energy and ensure the economy of the system while effectively protecting the benefits of market participants.

[0175] The above descriptions are merely embodiments of the present invention and are not intended to limit the patent scope of the present invention. Any equivalent transformations made using the contents of the present invention's specification and drawings, or directly or indirectly applied in related technical fields, are also included in the patent protection scope of the present invention.

Claims

1. A power system power planning method based on electricity-carbon-hydrogen synergy, characterized in that: The steps include: S1. Establishing a first objective function with the goal of minimizing the total investment cost of the power system during the system planning period, and setting an installed capacity constraint, a power margin constraint, and an annual investment net profit constraint subordinate to the first objective function; S2. Establishing a second objective function, wherein the second objective function includes a cost function with the goal of minimizing operating costs and carbon emission costs and a market clearing function with the goal of minimizing market transaction revenue; S3, creating a new energy output prediction error constraint corresponding to the power system, integrating the first objective function, the second objective function and the new energy output prediction error constraint, and obtaining a system planning model; S4. Obtain input variables and solve the system planning model.

2. The power system power supply planning method based on electricity-carbon-hydrogen synergy according to claim 1 is characterized in that: The first objective function is expressed as follows: min:f inv +f fix -f cap ; Among them, f inv ,f fix ,f cap Respectively represent investment cost, fixed maintenance cost and capacity compensation cost of thermal power units; Investment cost: Fixed maintenance costs: Capacity compensation costs for thermal power units: in, Respectively represent the collection of thermal power units, wind power, photovoltaic, electrolyzer and hydrogen storage tank to be built, Ω g ,Ω w ,Ω pv Respectively represent the collection of thermal power units, wind power and photovoltaic units in service, P i g , P i w , P i pv , P i PEM , P i HST Respectively represent the rated capacity of thermal power units, wind power, photovoltaic, electrolyzer and hydrogen storage tank, Represent the unit capacity investment costs of thermal power units, wind power, photovoltaics, electrolyzers and hydrogen storage tanks, respectively. Represent the fixed maintenance costs per unit capacity of thermal power units, wind power, photovoltaics, electrolyzers and hydrogen storage tanks, respectively. Represent the fixed maintenance costs per unit capacity of thermal power units, wind power, photovoltaics, electrolyzers and hydrogen storage tanks, respectively. It is a 0-1 integer variable, which represents the status of thermal power units, wind power, photovoltaic and hydrogen production and storage equipment respectively. The value of the thermal power units and renewable energy units in operation is 1. For the thermal power units, renewable energy units, electrolyzers and hydrogen storage tanks to be selected, when the value is 1, it means construction is in progress, and when the value is 0, it means no construction is in progress. is the unit capacity compensation price of thermal power units, P i g,com Indicates the compensation capacity of thermal power units, μ i g , μ i w , μ i pv , μ i PWM , μ i HST represents the capital recovery coefficient of thermal power units, wind power, photovoltaic, electrolyzer and hydrogen storage tank respectively, and i represents the equipment variable; and: Where r is the discount rate, N i Indicates the age of the equipment.

3. The power system power supply planning method based on electricity-carbon-hydrogen synergy according to claim 2 is characterized in that: The installed capacity constraints include the maximum construction capacity constraints of coal-fired power units, the maximum construction capacity constraints of photovoltaic power, the maximum construction capacity constraints of wind power, the maximum construction capacity constraints of electrolyzers and the maximum construction capacity constraints of hydrogen storage tanks.

4. The power system power supply planning method based on electricity-carbon-hydrogen synergy according to claim 2 is characterized in that: The power margin constraints include: Among them, Ω h ,Ω d Respectively represent the DC line and load node set, P i h,max , P i d,max They represent the maximum active transmission power of the DC line and the maximum load of the node, respectively, pv , χ w They represent the confidence capacity coefficients of photovoltaic and wind power respectively, and R is the reserve capacity coefficient.

5. The power system power supply planning method based on electricity-carbon-hydrogen synergy according to claim 2 is characterized in that: The annual net investment net profit constraints include: Among them, s and t represent the operation scenario and time period respectively, λ d , PEM , ccer Respectively represent the node marginal electricity price, the expected price of hydrogen and the clearing price, N s is the number of scenes, f s o 、f s car Respectively represent the operating cost and carbon emission cost of thermal power units, They represent the active output of thermal power units, photovoltaic units, and wind power units, the active load of the load node, and the active power of the electrolyzer.

6. The power system power supply planning method based on electricity-carbon-hydrogen synergy according to claim 2 is characterized in that: The step S2 comprises: S21. Create a cost function with the goal of minimizing operating costs and carbon emission costs: minf ope +f car ; Among them, Ω t ,Ω s Respectively represent the running time period and the running scene set, f ope 、f car Represent the total operating cost and total carbon emission cost of the system respectively, They represent the coefficients of the power generation cost of thermal power units, Indicates the active power and apparent power of the thermal power unit. They represent the constant term and slope of the CEI curve of thermal power units, is the industry benchmark value for thermal power units, O car represents the carbon emission quota price, It is a 0-1 integer variable, indicating the start and stop status of the thermal power unit. A value of 1 indicates that the unit is in the start-up state, and a value of 0 indicates that the unit is in the shutdown state. S22. Setting power balance condition constraints, unit operation constraints, DC operation constraints, line transmission power constraints, electrolyzer operation constraints, and hydrogen storage tank operation constraints that are subordinate to the cost function.

7. The power system power supply planning method based on electricity-carbon-hydrogen synergy according to claim 2 is characterized in that: The step S2 comprises: S23. Create a market clearing function with the goal of minimizing market transaction returns: in, Represent the buying and selling prices of renewable energy, Respectively represent the buying and selling volumes of market entities; S24. Setting a transaction quantity consistency constraint, an offset ratio upper limit constraint, a selling quantity constraint, and a carbon dioxide emission reduction constraint that are subordinate to the market clearing function.

8. The power system power supply planning method based on electricity-carbon-hydrogen synergy according to claim 1 is characterized in that: The creating of the new energy output prediction error constraint corresponding to the power system includes: Create a budget uncertainty set to characterize the error constraints on renewable energy output forecasts: in, represents the wind power prediction error, Photovoltaic prediction error, and are the boundary adjustment values ​​of the budget uncertainty set composed of the actual output of wind power and photovoltaic power, respectively, to control the conservatism of uncertain parameters, is the total wind and solar prediction error of the system; The number of wind turbines to be built. is the number of photovoltaics.

9. The method for power system power supply planning based on electricity-carbon-hydrogen synergy according to claim 1 is characterized in that: The system planning model: Among them, z is the investment and construction decision of thermal power units, wind power, photovoltaic and hydrogen production and storage equipment, f1(z) represents the first objective function, f2(y) is the objective function of the second stage, and y is the input variable of the second objective function. For The expected function of the maximum risk value under the conditions.

10. A power system power planning terminal based on electricity-carbon-hydrogen synergy, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, it implements the power system power planning method based on electricity-carbon-hydrogen synergy as described in any one of claims 1 to 9.

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